clear all
close all

load('QCSF_f.mat');
load('subject_specification.mat');

for ss = 1:8
        param_pre_t_f(ss,:) = 10.^(Training.pre_params{ss,1});
        param_post_t_f(ss,:) = 10.^(Training.post_params{ss,1});
        
        rt_pre_t_f(ss,1) = median(Training.pre_history{ss,1}(:,5));
        rt_post_t_f(ss,1) = median(Training.post_history{ss,1}(:,5));
        
        au_pre_t_f(ss,1) = Training.pre_aulcsf{ss,1};
        au_post_t_f(ss,1) = Training.post_aulcsf{ss,1};
        
        plot_pre_t_f(ss,:) = Training.pre_plot{ss,1}(:,2);
        plot_post_t_f(ss,:) = Training.post_plot{ss,1}(:,2);
        
        param_pre_t_n(ss,:) = 10.^(Training.pre_params{ss,2});
        param_post_t_n(ss,:) = 10.^(Training.post_params{ss,2});
        
        rt_pre_t_n(ss,1) = median(Training.pre_history{ss,2}(:,5));
        rt_post_t_n(ss,1) = median(Training.post_history{ss,2}(:,5));
        
        au_pre_t_n(ss,1) = Training.pre_aulcsf{ss,2};
        au_post_t_n(ss,1) = Training.post_aulcsf{ss,2};
        
        plot_pre_t_n(ss,:) = Training.pre_plot{ss,2}(:,2);
        plot_post_t_n(ss,:) = Training.post_plot{ss,2}(:,2);
        
        
        
        
        param_pre_ct_f(ss,:) = 10.^(ControlTraining.pre_params{ss,1});
        param_post_ct_f(ss,:) = 10.^(ControlTraining.post_params{ss,1});
        
        rt_pre_ct_f(ss,1) = median(ControlTraining.pre_history{ss,1}(:,5));
        rt_post_ct_f(ss,1) = median(ControlTraining.post_history{ss,1}(:,5));
        
        au_pre_ct_f(ss,1) = ControlTraining.pre_aulcsf{ss,1};
        au_post_ct_f(ss,1) = ControlTraining.post_aulcsf{ss,1};
        
        plot_pre_ct_f(ss,:) = ControlTraining.pre_plot{ss,1}(:,2);
        plot_post_ct_f(ss,:) = ControlTraining.post_plot{ss,1}(:,2);
        
        param_pre_ct_n(ss,:) = 10.^(ControlTraining.pre_params{ss,2});
        param_post_ct_n(ss,:) = 10.^(ControlTraining.post_params{ss,2});
        
        rt_pre_ct_n(ss,1) = median(ControlTraining.pre_history{ss,2}(:,5));
        rt_post_ct_n(ss,1) = median(ControlTraining.post_history{ss,2}(:,5));
        
        au_pre_ct_n(ss,1) = ControlTraining.pre_aulcsf{ss,2};
        au_post_ct_n(ss,1) = ControlTraining.post_aulcsf{ss,2};
        
        plot_pre_ct_n(ss,:) = ControlTraining.pre_plot{ss,2}(:,2);
        plot_post_ct_n(ss,:) = ControlTraining.post_plot{ss,2}(:,2);
        
        
        
        
        
        
        param_pre_c_f(ss,:) = 10.^(Control.pre_params{ss,1});
        param_post_c_f(ss,:) = 10.^(Control.post_params{ss,1});
        
        rt_pre_c_f(ss,1) = median(Control.pre_history{ss,1}(:,5));
        rt_post_c_f(ss,1) = median(Control.post_history{ss,1}(:,5));
        
        au_pre_c_f(ss,1) = Control.pre_aulcsf{ss,1};
        au_post_c_f(ss,1) = Control.post_aulcsf{ss,1};
        
        plot_pre_c_f(ss,:) = Control.pre_plot{ss,1}(:,2);
        plot_post_c_f(ss,:) = Control.post_plot{ss,1}(:,2);
        
        param_pre_c_n(ss,:) = 10.^(Control.pre_params{ss,2});
        param_post_c_n(ss,:) = 10.^(Control.post_params{ss,2});
        
        rt_pre_c_n(ss,1) = median(Control.pre_history{ss,2}(:,5));
        rt_post_c_n(ss,1) = median(Control.post_history{ss,2}(:,5));

        au_pre_c_n(ss,1) = Control.pre_aulcsf{ss,2};
        au_post_c_n(ss,1) = Control.post_aulcsf{ss,2};
        
        plot_pre_c_n(ss,:) = Control.pre_plot{ss,2}(:,2);
        plot_post_c_n(ss,:) = Control.post_plot{ss,2}(:,2);
end
